The use of handwriting input in electronic devices poses a set of problems, e.g. due to the fact that handwriting is individual and the fact that it is sometimes difficult to distinguish different handwritten characters from each other. Different systems have been developed for the purpose of facilitating input of characters into electronic devices by means of handwriting instead of typing on keyboards, key pads and the like.
In efforts to increase the handwriting recognition accuracy, different ways to distinguish different characters have been suggested. For example, some systems require the user to write characters in a special way, and other include means which are able to “learn” the handwriting of individual users.
Handwriting recognition may also take into consideration information regarding the context in which characters occur.
The US application with publication no. U.S. 2004/0017946 discloses a handwritten Chinese character input method and system including a list of probable Chinese characters which is based on the key strokes input. As more key strokes are input, the list of Chinese character is adjusted and when the desired Chinese character appears in the list, the user can pick the character by means of a selection movement, such as a mouse or stylus or finger tapping.
The European patent EP 0 686 291 discloses a method of handwriting recognition which uses a dictionary for recognizing an input handwritten word. Candidate characters are identified for each character of the input handwritten word and combinations of the candidate characters are compared with entries in the dictionary to provide candidate words that might represent the input. Furthermore, a most likely character string is identified as a combination of candidate characters that has a highest combined likelihood of being correct without regard to the dictionary. A list is the provided comprising the candidate words and the most likely character string if it is not one of the candidate words.
The recognition of words by means of combination of different candidate characters requires a large amount of processing and a very large dictionary. Hence there exists a need for handwriting recognition which alleviates these drawbacks whilst still maintaining good recognition accuracy.